Principal Associate, Data Scientist - Mainstreet Acquisitions

Capital One•McLean, VA

18h•$161,800 - $201,400

About The Position

Principal Associate, Data Scientist - Mainstreet Acquisitions Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. Team Description Valuations team is a multi-disciplinary team focused on the development, deployment, model governance, and risk management of valuations model in credit underwriting. Our mission is to bring real-time, personalized offers to our customers - via innovation and optimization in our valuations modeling system. We work with partners from across the enterprise to build data and modeling products that enable best in class credit analysis and customer-facing decisioning. Underwriting innovation is a key source of Capital One’s competitive advantage - it is in our DNA. Our team continues to push that competitive edge through the use of new data and advanced modeling techniques. Building the capabilities that the enterprise needs is a challenging long term project; the prize is big and there are plenty of opportunities to deliver value on the way. To bring our vision to life, as a model developer and data scientist, you can expect to: Conduct model development, experimenting with various statistical methodologies to improve model performance; Leverage alternative data sources along with various feature selection and engineering techniques to enhance in market models; Develop next-gen credit underwriting models; Partner with key stakeholders across the organization to establish standards for the new modeling approaches that are consistent with our values; Push the envelope with new data and new modeling approaches to improve our lending decisions. Our team’s work is both intellectually demanding and highly collaborative. As part of an enterprise team delivering new capabilities, you will be working across: LOB underwriting teams, various DS/DA teams, enterprise platform teams, enterprise data team, tech teams, legal and compliance teams, consumer credit risk management, model risk office, and enterprise data risk management. Great team culture is profoundly important to us: we want everyone to feel they are doing meaningful and enjoyable work; we are informal and indifferent to hierarchy; we actively encourage new ideas and new ways of doing things; we respect each other’s perspectives and preferences. Role Description In this role, you will: Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love Leverage a broad stack of technologies — Python, Conda, AWS, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation Flex your interpersonal skills to translate the complexity of your work into tangible business goals The Ideal Candidate is: Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea. Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms. Statistically-minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning. A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.

Requirements

Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics
A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics
A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)

Nice To Haves

Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
At least 1 year of experience working with AWS
At least 3 years’ experience in Python, Scala, or R
At least 3 years’ experience with machine learning
At least 3 years’ experience with SQL

Responsibilities

Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
Leverage a broad stack of technologies — Python, Conda, AWS, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
Flex your interpersonal skills to translate the complexity of your work into tangible business goals

Benefits

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.

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